Sequential anomaly detection with labeling costs

In a number of data analytics domains, there is a need for detecting the situations when something outside of the normal conditions is happening. The goal of this project is to develop novel algorithms that learn to distinguish these normal and anomalous patterns through minimal interaction with a human user, while allowing complex data patterns […]

Read More